We are excited to announce the 9th annual HPCC Systems Community Summit will once again be held virtually this October! This year's event is free to attend and open to all users of HPCC Systems throughout the open source community.
Elsevier, Plant Science, Volume 324, November 2022, 111427
In this study, ornamental tobacco floral nectar was found to be the source of numerous peptides, some showing antifungal or antibacterial activities. The characterization of these peptides could open new roads of research with potential applications in crop protection and pollination, public health and, more generally, biotechnologies.
Community Care, uan Cuong Nguyen, Thi Thanh Huyen Nguyen, Quoc Ba Tran, Xuan-Thanh Bui, Huu Hao Ngo, Dinh Duc Nguyen,Chapter 21 - Artificial intelligence for wastewater treatment,Editors: Xuan-Thanh Bui, Dinh Duc Nguyen, Ashok Pandey,Advances in Biological Wastewater Treatment Systems,Elsevier,2022,Pages 587-608,ISBN 9780323998741
This chapter advances SDG 6 and 9 by outlining state-of-the-art development in the use of applied AI for wastewater treatment plants (WWTPs) with a focus on output, algorithms, data, and performance.
Elsevier, Sai Karthik Cheemalamarry, Vinayak Sharma, Yaddanapudi Varun, I. Sreedhar, Satyapaul A. Singh,10 - Recent advances of nanotechnology in water remediation,Editor(s): Noel Jacob Kaleekkal, Prasanna Kumar S. Mural, Saravanamuthu Vigneswaran,In Micro and Nano Technologies,Nano-Enabled Technologies for Water Remediation,Elsevier,2022,Pages 311-333,ISBN 9780323854450
This chapter contributes to SDG 6 by providing up-to-date information on nanomaterial potential application in water remediation.
A Viewpoint, in the context of SDG 3 and 9, exploring the impact and potential of China's Smart Eldercare model, which harnesses digital technologies to improve the quality of life of China's fast-expanding ageing population, including nearly 10 million people with Alzheimer's disease.
Elsevier, Telematics and Informatics Reports, Volume 7, September 2022, 100013
The authors propose a multi-attribute group decision-making (MAGDM) approach to evaluate and select digital voting tools that facilitate public participation in urban transport decision-making.